which means that from all the feasible distributions \(\mathcal {P}\)  we must find a distribution, which we call \(\mathcal {P_{ME}}\) , that maximizes the entropy subject to specific constraints.
Following Jayne's [1]} interpretation of the principle, \(ME\)  is the least biased distributions encoding all the information that we have about the system.
In other words, in absence of a mechanistic model, we consider \(\mathcal {P_{ME}}\)  to be our best guest of the real \(\mathcal {P}\) , given the available information.
